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Gartner recently published its 2019 Magic Quadrant for Data Science and Machine Learning Platforms. You can secure a copy of the report from Gartner if you are a client, or read it for free here, courtesy of DataRobot. (Registration required.) Here’s how Gartner positioned the 17 vendors that made it into the MQ: Back in October, I wrote my predictions for

Well, 2018 is dead and gone. Time to take a look back at the year in AI/ML. A reminder that I work for DataRobot. This is my personal blog. Opinions are mine. On the Move It’s hard to believe that Amazon Web Services introduced Amazon SageMaker just a year ago, but here we are. AWS moved aggressively to enhance the

The die is cast. Last month, Gartner selected 16 vendors to include in its 2019 Magic Quadrant for Data Science and Machine Learning. Now, as Gartner prepares to publish the report early next year, I think it will be fun to make some predictions about how each vendor will fare. Some ground rules. I’m not going to talk about DataRobot,

Forrester just published two “Wave” reports for predictive analytics and machine learning. The first, covering “multi-modal” solutions, is available here for free. A second report, covering notebook-based solutions, is available here (registration required.) Forrester plans to publish a third report, covering automated machine learning vendors, in 2019. Kudos to Forrester for understanding the diversity of the data science tools market.

Gartner just released the 2018 Magic Quadrant for Data Science and Machine Learning Platforms. You can get a copy directly from Gartner if you’re a client, or you can get one here, courtesy of RapidMiner. Here are the 2017 and 2018 MQs side by side: Here are my comments on the 2017 and 2016 MQs. For five observations about the 2018 MQ,

There are two big stories this week: Apache Spark 2.0 and Apache Mesos 1.0. There’s also a new release from Kylin, and a nice crop of explainers. IEEE Spectrum publishes its third annual ranking of top programming languages, based on twelve metrics drawn from Google Search, Google Trends, Twitter, GitHub, Stack Overflow, Reddit, Hacker News, CareerBuilder, Dice, and the IEEE